diff options
Diffstat (limited to 'src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp | 196 |
1 files changed, 140 insertions, 56 deletions
diff --git a/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp b/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp index 00c3f98334..1a3810fb56 100644 --- a/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp +++ b/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2017-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -21,55 +21,143 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "arm_compute/core/NEON/kernels/NEROIPoolingLayerKernel.h" +#include "src/core/NEON/kernels/NEROIPoolingLayerKernel.h" -#include "arm_compute/core/AccessWindowStatic.h" -#include "arm_compute/core/CPP/Validate.h" -#include "arm_compute/core/Error.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/ITensor.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" + +#include "src/core/CPP/Validate.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" #include "support/ToolchainSupport.h" #include <cfloat> -#include <cmath> namespace arm_compute { +namespace +{ +Status validate_arguments(const ITensorInfo *input, + const ITensorInfo *rois, + const ITensorInfo *output, + const ROIPoolingLayerInfo &pool_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output, rois); + + //Validate arguments + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(rois, DataType::U16); + ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(0) != 5); + ARM_COMPUTE_RETURN_ERROR_ON(rois->num_dimensions() > 2); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F32, DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0)); + + if (output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) != pool_info.pooled_width()) || + (output->dimension(1) != pool_info.pooled_height())); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != output->dimension(2)); + ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(1) != output->dimension(3)); + } + + return Status{}; +} + +/** Evaluate number needing to be stored in output tensor as quantized format. + * + * @param[in] input Source tensor. Data types supported: QASYMM8 + * @param[out] output Destination tensor. Where output value will be stored, same datatype as input + * @param[in] region_start_x Beginning region of x coordinate of pooling region + * @param[in] region_start_y Beginning region of y coordinate of pooling region + * @param[in] region_end_x End of pooling region, x coordinate + * @param[in] region_end_y End of pooling region, y coordinate + * @param[in] fm Channel index of coordinate in output Tensor to store value + * @param[in] px Width index of coodinate in output Tensor to store value + * @param[in] py Height index of coordinate in output Tensor to store value + * @param[in] roi_batch Index of image to perform Pooling on in input Tensor + * @param[in] roi_indx Index of image of coordinate in output Tensor to store value + */ +template <typename T> +void template_eval(const ITensor *input, + const ITensor *output, + int region_start_x, + int region_start_y, + int region_end_x, + int region_end_y, + int fm, + int px, + int py, + int roi_batch, + int roi_indx) +{ + if ((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) + { + *reinterpret_cast<T *>(output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = 0; + } + else + { + T curr_max = std::numeric_limits<T>::lowest(); // Min value of typename T + for (int j = region_start_y; j < region_end_y; ++j) + { + for (int i = region_start_x; i < region_end_x; ++i) + { + const auto val = *reinterpret_cast<const T *>(input->ptr_to_element(Coordinates(i, j, fm, roi_batch))); + curr_max = std::max(val, curr_max); + } + } + + // if quantized datatype, requantize then store in output tensor + if (is_data_type_quantized(input->info()->data_type())) + { + // covert qasymm to new output quantization scale and offset + UniformQuantizationInfo uqinfo = compute_requantization_scale_offset( + input->info()->quantization_info().uniform(), output->info()->quantization_info().uniform()); + *reinterpret_cast<T *>(output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = + quantize_qasymm8(curr_max, uqinfo); + } + else + { + *reinterpret_cast<T *>(output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = curr_max; + } + } +} +} // namespace + NEROIPoolingLayerKernel::NEROIPoolingLayerKernel() : _input(nullptr), _rois(nullptr), _output(nullptr), _pool_info(0, 0, 0.f) { } -void NEROIPoolingLayerKernel::configure(const ITensor *input, const ITensor *rois, ITensor *output, const ROIPoolingLayerInfo &pool_info) +Status NEROIPoolingLayerKernel::validate(const ITensorInfo *input, + const ITensorInfo *rois, + const ITensorInfo *output, + const ROIPoolingLayerInfo &pool_info) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, rois, output, pool_info)); + return Status{}; +} + +void NEROIPoolingLayerKernel::configure(const ITensor *input, + const ITensor *rois, + const ITensor *output, + const ROIPoolingLayerInfo &pool_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, rois); //Validate arguments - ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), rois->info(), output->info()); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(rois, 1, DataType::U16); - ARM_COMPUTE_ERROR_ON(rois->info()->dimension(0) != 5); - ARM_COMPUTE_ERROR_ON(rois->info()->num_dimensions() > 2); - ARM_COMPUTE_ERROR_ON_CPU_F16_UNSUPPORTED(input); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16); - ARM_COMPUTE_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0)); - - if(output->info()->total_size() != 0) - { - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pool_info.pooled_width()) || (output->info()->dimension(1) != pool_info.pooled_height())); - ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != output->info()->dimension(2)); - ARM_COMPUTE_ERROR_ON(rois->info()->dimension(1) != output->info()->dimension(3)); - } + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), rois->info(), output->info(), pool_info)); // Output auto initialization if not yet initialized - TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), rois->info()->dimension(1)); - auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type()); + TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), + rois->info()->dimension(1)); + + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), + output->info()->quantization_info()); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pool_info.pooled_width()) || (output->info()->dimension(1) != pool_info.pooled_height())); + ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pool_info.pooled_width()) || + (output->info()->dimension(1) != pool_info.pooled_height())); // Set instance variables _input = input; @@ -82,10 +170,6 @@ void NEROIPoolingLayerKernel::configure(const ITensor *input, const ITensor *roi window.set(Window::DimX, Window::Dimension(0, rois->info()->dimension(1))); window.set(Window::DimY, Window::Dimension(0, 1)); - Coordinates coord; - coord.set_num_dimensions(output->info()->num_dimensions()); - output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); - INEKernel::configure(window); } @@ -106,9 +190,10 @@ void NEROIPoolingLayerKernel::run(const Window &window, const ThreadInfo &info) const int pooled_h = _pool_info.pooled_height(); const float spatial_scale = _pool_info.spatial_scale(); - const auto *rois_ptr = reinterpret_cast<const uint16_t *>(_rois->buffer()); + const auto *rois_ptr = reinterpret_cast<const uint16_t *>(_rois->buffer()); + const auto data_type = _input->info()->data_type(); - for(int roi_indx = roi_list_start; roi_indx < roi_list_end; ++roi_indx) + for (int roi_indx = roi_list_start; roi_indx < roi_list_end; ++roi_indx) { const unsigned int roi_batch = rois_ptr[values_per_roi * roi_indx]; const auto x1 = rois_ptr[values_per_roi * roi_indx + 1]; @@ -123,44 +208,43 @@ void NEROIPoolingLayerKernel::run(const Window &window, const ThreadInfo &info) const int roi_height = std::max(support::cpp11::round((y2 - y1) * spatial_scale), 1.f); // Iterate through all feature maps - for(int fm = 0; fm < fms; ++fm) + for (int fm = 0; fm < fms; ++fm) { // Iterate through all output pixels - for(int py = 0; py < pooled_h; ++py) + for (int py = 0; py < pooled_h; ++py) { - for(int px = 0; px < pooled_w; ++px) + for (int px = 0; px < pooled_w; ++px) { auto region_start_x = static_cast<int>(std::floor((static_cast<float>(px) / pooled_w) * roi_width)); - auto region_end_x = static_cast<int>(std::floor((static_cast<float>(px + 1) / pooled_w) * roi_width)); - auto region_start_y = static_cast<int>(std::floor((static_cast<float>(py) / pooled_h) * roi_height)); - auto region_end_y = static_cast<int>(std::floor((static_cast<float>(py + 1) / pooled_h) * roi_height)); + auto region_end_x = + static_cast<int>(std::floor((static_cast<float>(px + 1) / pooled_w) * roi_width)); + auto region_start_y = + static_cast<int>(std::floor((static_cast<float>(py) / pooled_h) * roi_height)); + auto region_end_y = + static_cast<int>(std::floor((static_cast<float>(py + 1) / pooled_h) * roi_height)); region_start_x = std::min(std::max(region_start_x + roi_anchor_x, 0), width); region_end_x = std::min(std::max(region_end_x + roi_anchor_x, 0), width); region_start_y = std::min(std::max(region_start_y + roi_anchor_y, 0), height); region_end_y = std::min(std::max(region_end_y + roi_anchor_y, 0), height); - // Iterate through the pooling region - if((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) - { - *reinterpret_cast<float *>(_output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = 0; - } - else + switch (data_type) { - float curr_max = -FLT_MAX; - for(int j = region_start_y; j < region_end_y; ++j) - { - for(int i = region_start_x; i < region_end_x; ++i) - { - const auto val = *reinterpret_cast<const float *>(_input->ptr_to_element(Coordinates(i, j, fm, roi_batch))); - curr_max = std::max(val, curr_max); - } - } - *reinterpret_cast<float *>(_output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = curr_max; + case DataType::F32: + template_eval<float>(_input, _output, region_start_x, region_start_y, region_end_x, + region_end_y, fm, px, py, roi_batch, roi_indx); + break; + case DataType::QASYMM8: + template_eval<qasymm8_t>(_input, _output, region_start_x, region_start_y, region_end_x, + region_end_y, fm, px, py, roi_batch, roi_indx); + break; + default: + ARM_COMPUTE_ERROR("DataType not Supported"); + break; } } } } } } -} // namespace arm_compute
\ No newline at end of file +} // namespace arm_compute |